Evidence map›Paper›PMID 32322672›Full record

ReviewCannabis and cannabinoid research2020

Endocannabinoids and Stroke Prevention: Review of Clinical Studies.

Eugene L Scharf, Jon O Ebbert

Open access · greenAbstract readReview
In one paragraph

Review in Cannabis and cannabinoid research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Eugene L ScharfDepartment of Neurology, Mayo Clinic, Rochester, Minnesota.
Jon O EbbertCommunity Internal Medicine, Mayo Clinic, Rochester, Minnesota.
Mayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The societal burden of ischemic stroke suggests a need for additional therapeutic categories in stroke prevention. Modulation of the endocannabinoid system (ECS) is a rational target for stroke prevention because of its effects on inflammation, vascular tone, and metabolic balance, all well-described stroke risk factors. In this article, we summarize the existing ECS clinical studies in human subjects' research as they relate to conventional vascular risk factors associated with ischemic stroke. To date, 2-arachidonoylglycerol (2-AG) derivative endocannabinoids are consistently reported to be elevated in insulin resistance, whereas the N-arachidonoylethanolamine (AEA) endocannabinoid derivatives are elevated in obesity. The ECS role in metabolic health should examine the effects of 2-AG reduction and AEA augmentation as a means of stroke risk reduction. Cannabinoid receptors are reported on macrophages within atherosclerotic plaques and suggest a role for immunomodulation as a therapeutic for atherosclerosis through both peripheral immune cell CB1 antagonism and/or CB2 agonist. The effects of ECS on hypertension, smoking, physical activity, obstructive sleep apnea, heart failure, and atrial fibrillation are incompletely described and deserve further study. A limitation to ECS research is significant overlap with noncannabinoid molecular targets. Further exploration of the ECS needs to include the larger metabolomics context for a greater understanding of its therapeutic potential. Clinical translational studies in stroke prevention should be directed at ECS in metabolic balance and atherosclerosis.

Indexed as

2-AGAEAanandamidecannabinoid receptorsendocannabinoid systemstroke prevention

Identifiers

PMID32322672
PMCPMC7173678
OpenAlexW2940815572

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.